Do you spend hours cleaning up and integrating ‘omics data, yet still feel like you are drowning in it?
‘Omics data is a powerful resource to help drive innovation in biomarker and target discovery. If you work in drug development, you probably explore potential therapies by using ‘omics data to find new targets and indications. Yet it can be daunting to process, integrate and clean the data to make it meaningful. You’re probably working with data from both public portals and your internally-generated sources, each with its own sets of metadata and respective vocabularies. Perhaps it comes from several different drug discovery programs representing various diseases. The sheer volume and heterogeneity within ‘omics datasets can create a discouraging barrier to drawing meaningful conclusions.
Boost your bioinformatics capabilities
Have you ever thought of seeking the expertise and services of an experienced bioinformatics team to extend and speed up your ‘omics data processing capabilities?
QIAGEN Discovery Bioinformatics Services has the tools, knowledge and resources to help you quickly unravel the biology hidden in your ‘omics data. We supplement your workforce with experts from our bioinformatics team, including Ph.D.-qualified scientists, developers and project managers to provide a customized solution for your project. We do everything from secondary analysis services to in-depth analysis of biological data. We also take on high-quality content curation of literature, datasets and pathways. We can even build custom databases, which are specific collections of integrated ‘omics data with manually curated metadata.
Our services team helps biologists and bioinformaticians like you quickly answer questions relevant to your biomarker and target discovery projects. We do this by using our state-of-the-art software tools and high-quality manually curated content to query your ‘omics data to help answer your hypothesis-generating questions, such as:
- What is the expression pattern of my target(s)?
- In what tissue or disease is my target differentially expressed?
- What is the expression signature for my disease state?
- What are the different cell types across datasets, and how abundant are each one?
- What is the differential gene expression of monocytes in disease vs. control samples?
Once we run these queries, we can perform deeper meta-analyses on data collections to help you make more accurate hypotheses based on the biological context. Our queries and analyses save you countless hours organizing and visualizing internal pipelines and results, taking you directly down the biological path that makes most sense.
Example service project
A typical transcriptomic project that we take on is processing and storing bulk RNA-seq datasets, including single-cell RNA-seq. Sound familiar? Our QIAGEN Discovery Bioinformatics Services team will create a customized unified pipeline script to process your data and store it in a database framework. We pay special attention to statistical analysis, which can often be tricky when working with transcriptomic data. That’s because this type of data is often generated from heterogeneous samples composed of multiple cell types, and the counts data from a sample represents the average gene expression across all cell types. This heterogeneity is a major hurdle in statistical analysis. Differences in cell type proportions may prevent or bias the detection of cell type-specific transcriptional programs. To manage such challenges, our services team:
- Performs deconvolution of different cell types in the datasets and stores cell type abundance at sample-level resolution
- Provides a framework to run the samples in parallel using Amazon workspace to store the data
- Manually curates the metadata with controlled vocabularies in order to query and return quality-controlled samples and data
- Adds statistical comparisons using the curated metadata
Figure 1. Workflow for processing bulk RNA-seq data.
Quickly get the output you need
On all our projects, we work with you to determine the output and deliverables that best fit your needs. A typical example of what we provide for bulk RNA-seq data processing and storing is:
- A customized integrated ‘omics data collection based on your internal data (‘internal Land’)
- A centralized database that biologists use for disease-focused queries, sources from your internal Land
- Custom scripts that enable analyses of both human and non-human data
- Combined information from multiple studies into a unified picture of biomarkers and disease signatures to help validate hypotheses
- Differential gene expression analysis to assess changes of candidate target gene related to a disease
- Signature-based analysis to gain insights into which diseases are relevant for target genes
- Assessment of relative cell type (cell state) abundance at sample-level resolution for multiple tissue types
- Investigation of differentially expressed genes and signatures at cell-type resolution
By working with QIAGEN Discovery Bioinformatics Services on projects like bulk RNA-seq data processing, you’ll save time and increase accuracy. We help you quickly prioritize drug targets, biomarkers and compounds so you can readily gain a more robust and insightful understanding of complex diseases, to drive your next discovery.
Would you like to reduce the burden of working with ‘omics data to more quickly reach your next biomarker or target discovery? Could you use support with RNA-seq data processing and analysis? Let QIAGEN Discovery Bioinformatics Services lend a helping hand. Learn more about our range of bioinformatics services to extend and scale your in-house resources with our expertise and tailored bioinformatics services. Contact us today at email@example.com to get your next project started. Together, we’ll tame the ‘omics data beast.